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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/egusphere-2026-3013</article-id>
<title-group>
<article-title>An adaptive unstructured grid for HF radar current mapping based on constrained k-means clustering</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Doronzo</surname>
<given-names>Bartolomeo</given-names>
<ext-link>https://orcid.org/0000-0002-0418-1932</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Taddei</surname>
<given-names>Stefano</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Brandini</surname>
<given-names>Carlo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Istituto di Scienze Marine ISMAR-CNR, 50019 Firenze, Italy</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Consorzio LaMMA, 57126 Livorno, Italy</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Consorzio LaMMA, 50019 Firenze, Italy</addr-line>
</aff>
<pub-date pub-type="epub">
<day>05</day>
<month>06</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>23</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Bartolomeo Doronzo et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3013/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3013/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3013/egusphere-2026-3013.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3013/egusphere-2026-3013.pdf</self-uri>
<abstract>
<p>High-Frequency (HF) radar systems provide high-resolution observations of surface currents in coastal oceans, but their effective representation strongly depends on the spatial discretization used to combine radial measurements. Standard regular grids impose a uniform resolution across the domain, despite the highly heterogeneous sampling geometry of HF radar systems, leading to inefficient use of observations and limited effective resolution in key coastal regions.&lt;/p&gt;
&lt;p&gt;We propose a fully automated, non-uniform adaptive gridding framework specifically designed for HF radar applications. The method defines grid nodes directly from the spatial distribution of radar observations, redistributing resolution according to local data availability while preserving a consistent discretization of the domain. The resulting unstructured grid naturally refines resolution in densely sampled near‑coastal areas and adopts coarser spacing offshore. Grid nodes can be associated with either Voronoi polygons or equivalent‑area circular supports, providing flexibility in the geometrical representation of spatial support without altering node placement.&lt;/p&gt;
&lt;p&gt;The proposed discretization yields a more realistic spatial representation of HF radar surface currents, reducing artefacts linked to uniform gridding and enhancing the visibility of coastal circulation structures. Comparison with surface drifter observations indicates that this improved spatial coherence is achieved without compromising overall reconstruction skill. The framework provides a radar‑aware basis for current mapping, interpolation, and data assimilation applications where geometrical consistency and adaptive resolution are critical.</p>
</abstract>
<counts><page-count count="23"/></counts>
</article-meta>
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